Identification of Canadian durum wheat [<i>Triticum turgidum</i> L. subsp. <i>durum</i> (Desf.) Husn.] cultivars using AFLP and their STS markers
Bibliographic record
Abstract
We have developed two identification schemes for currently registered Canadian cultivars of durum wheat [Triticum turgidum L. subsp. durum (Desf) Husn.] based on cultivar-specific amplified restriction fragment polymorphism (AFLPJ) and their sequence tagged sites (STS) markers. Each identification key required seven markers. Transformation of AFLPs into STS markers was done in order to develop a PCR-based identification assay, which was cost effective and required minimal technical expertise. A cultivar diagnostic PCR assay was carried out for each STS primer pair. Five STS primers showed polymorphism among cultivars, but 60% of STS primers (7 out of 12) did not produce any polymorphism. The PCR products of the latter primers were digested with selected restriction enzymes resulting in restriction fragment polymorphism for two more loci. An STS-based identification key was generated for cultivar identification based on either the presence/absence of a DNA band or the presence/absence of a restriction enzyme recognition site after digestion of the PCR products with a restriction enzyme. DNA-based markers can be used as an efficient alternative to morphological traits for cultivar identification and finger printing at any stage of plant development. Moreover, an STS-based assay can be used with a minute amount of plant tissue such as fraction of a seed. Key words: Amplified restriction fragment polymorphism (AFLP), sequence tagged sites (STS), cloning, identification, durum wheat
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".